Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/nicepkg/ai-workflow/transcribe-and-analyzenpx skills add nicepkg/ai-workflow --skill transcribe-and-analyzegit clone --depth 1 https://github.com/nicepkg/ai-workflowWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/nicepkg/ai-workflow/transcribe-and-analyze)<a href="https://agentmods.dev/skills/nicepkg/ai-workflow/transcribe-and-analyze"><img src="https://agentmods.dev/badge/skills/nicepkg/ai-workflow/transcribe-and-analyze.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00053 | $0.01454 |
| Opus 5 | $0.00026 | $0.00727 |
| Sonnet 5 | $0.00011 | $0.00291 |
| Haiku 4.5 | $0.00005 | $0.00145 |
Grade A, and why
transcribe-and-analyze scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- transcribe-and-analyze — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 236 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Transcribe and Analyze
Local transcription of audio/video content using WhisperKit. Analysis is available on request using OpenAI or local Ollama.
Capabilities
- Transcription - Convert audio/video URLs to text using WhisperKit (runs locally, always available)
- Analysis - Extract insights from transcripts (only when user asks for it, supports OpenAI or Ollama)
Quick Start
Transcribe Only
python3 scripts/transcribe.py "https://youtube.com/watch?v=..."
Transcribe + Analyze (OpenAI)
python3 scripts/transcribe.py "https://youtube.com/watch?v=..."
python3 scripts/analyze_transcript.py whisper-transcriptions/video.md
Transcribe + Analyze (Local)
python3 scripts/transcribe.py "https://youtube.com/watch?v=..."
python3 scripts/analyze_transcript.py whisper-transcriptions/video.md --local
Transcription
Script Options
# Basic
python3 scripts/transcribe.py "URL"
# Custom output directory
python3 scripts/transcribe.py "URL" --output-dir "/path/to/save"
# Higher accuracy (slower)
python3 scripts/transcribe.py "URL" --model medium
# Without timestamps
python3 scripts/transcribe.py "URL" --no-timestamps
# Custom filename
python3 scripts/transcribe.py "URL" --filename "my-transcription.md"
Whisper Models
| Model | Speed | Accuracy | Use Case |
|---|---|---|---|
tiny |
Fastest | Lowest | Quick drafts, testing |
base |
Fast | Reasonable | Simple content |
small |
Balanced | Good | Default - most use cases |
medium |
Slower | High | Lectures, important content |
large |
Slowest | Highest | Critical accuracy needed |
Dependencies
- yt-dlp -
pip install yt-dlporbrew install yt-dlp - whisperkit-cli - https://github.com/argmaxinc/WhisperKit
Script checks for these and provides install instructions if missing.
Output
Transcriptions save to ./whisper-transcriptions/ as markdown:
# Transcription
**Source:** https://youtube.com/watch?v=example
**Transcribed:** 2025-01-15 14:30:00
**Tool:** WhisperKit
---
[00:00:00.000 --> 00:00:05.000] Welcome to this video...
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 236 lines · 53 tokens per session scan A 7daa3f4586e9
transcribe-and-analyze is a skill published in the GitHub repository nicepkg/ai-workflow (282 stars, last pushed 7mo ago), licensed MIT. It adds 53 tokens to every session and 1,454 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
当用户需要对PDF文件进行任何操作时，请使用此技能。包括从 PDF 中读取或提取文本/表格、合并多个 PDF、拆分 PDF、旋转页面、添加水印、创建新PDF、填写PDF表单、加密/解密 PDF、提取图片，以及对扫描版 PDF 进行 OCR 使其可搜索。如果用户提到 .pdf 文件或要求生成 PDF，请使用此技能。.
pptx
当涉及到 .pptx 文件的任何操作时使用此技能——无论是作为输入、输出还是两者兼有。包括：创建幻灯片、演示文稿或路演材料；读取、解析或提取任何 .pptx 文件中的文本（即使提取的内容将用于其他地方，如邮件或摘要）；编辑、修改或更新现有演示文稿；合并或拆分幻灯片文件；处理模板、布局、演讲者备注或批注。当用户提到“演示文稿”、”幻灯片“、”PPT“或引用 .pptx 文件名时触发，无论他们之后打算如何使用内容。如果需要打开、创建或操作 .pptx 文件，就使用此技能。.
nano-pdf
Edits PDF files using natural-language instructions via the nano-pdf CLI. Supports modifying text, changing titles, fixing typos, and updating content on specific pages. Use when the user wants to edit a PDF, modify PDF content, update PDF text, fix a typo in a PDF, change a PDF title, or rewrite part of a PDF page.
hive.pdf
Read, write, merge, split, rotate, watermark, encrypt, and OCR PDF files using Python (pypdf, pdfplumber, reportlab, pypdfium2) and command-line tools (poppler-utils, qpdf). Use when the user asks to extract text/tables/images from a PDF, create or modify a PDF, combine or split PDFs, OCR a scanned PDF…
pdf-toolkit
Structured .pdf operations: extract text/tables, merge pages from multiple PDFs, split a PDF by page ranges, fill PDF form fields, and generate fresh PDFs from JSON. Trigger when the user wants programmatic PDF work without natural-language rewriting — examples: pull tables from a report, combine three PDFs, extract…
sn-ppt-entry
Entry point for PPT generation. Asks the user to choose a mode (fast, standard, or creative), then collects role / audience / scene / pagecount as needed. For standard mode, also asks how images should be sourced (AI generation, web search, or none), whether charts should use AI-generated infographics or ECharts, and…